Cross-source Point Cloud Registration: Challenges, Progress and Prospects
This is an incremental review paper that synthesizes existing research for researchers and practitioners in 3D computer vision and sensor fusion.
The paper provides a systematic review of cross-source point cloud registration, addressing the problem of aligning point clouds from different 3D sensors like Kinect and LiDAR to enable generalized applications, but does not present new experimental results or concrete numbers.
The emerging topic of cross-source point cloud (CSPC) registration has attracted increasing attention with the fast development background of 3D sensor technologies. Different from the conventional same-source point clouds that focus on data from same kind of 3D sensor (e.g., Kinect), CSPCs come from different kinds of 3D sensors (e.g., Kinect and { LiDAR}). CSPC registration generalizes the requirement of data acquisition from same-source to different sources, which leads to generalized applications and combines the advantages of multiple sensors. In this paper, we provide a systematic review on CSPC registration. We first present the characteristics of CSPC, and then summarize the key challenges in this research area, followed by the corresponding research progress consisting of the most recent and representative developments on this topic. Finally, we discuss the important research directions in this vibrant area and explain the role in several application fields.